
All the results of SchNet and DimeNet++ are directly adopted from the OC20 paper [1]}. These energy-centric models are trained only on atomic forces, although in principle, they can be aso trained on per-system energy. [1]} report that training on forces and energy seperately achieves better performance on each task compared to joint training.
For the GNS model, we reproduce the original model architecture ourselves based on the feedback from the original author of GNS [3]}. Refer to Appendix  for implementation details. On the GNS model, we apply the same training strategies as ForceNet.
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